The existing original BP neural network models for wood performance prediction have low fitting accuracy and imprecise results. We propose a nonlinear, adaptive grouping gray wolf optimization (NAGGWO)-BP model prediction. Firstly, the (GWO) algorithm is optimized. CPM mapping (the Chebyshev method combined with piecewise followed by mod operation) to generate initial populations improve popula...

Abstract Recently, integrated machine learning (ML) metaheuristic algorithms, such as the artificial bee colony (ABC) algorithm, genetic algorithm (GA), gray wolf optimization (GWO) particle swarm (PSO) and water cycle (WCA), have become predominant approaches for landslide displacement prediction. However, these algorithms suffer from poor reproducibility across replicate cases. In this study,...

This work proposes a metaheuristic-based approach to hyperparameter selection in multilayer perceptron classify EMG signals. The main goal of the study is improve performance model by optimizing four important hyperparameters: number neurons, learning rate, epochs, and training batches. proposed this shows that optimization using particle swarm gray wolf optimizer significantly improves classif...

www.sciencemag.org SCIENCE VOL 325 3 JULY 2009 5 COVER The Phoenix spacecraft on the martian polar plains (68°N latitude). The footpad at the bottom is about 1 meter below the spacecraft deck seen at the lower left. Overlaid images are trenches dug to either nearly pure water ice or ice-cemented soil. Analyses of samples taken from these trenches give clues to the history of the region. Results...

In the traditional quantum wolf pack algorithm, distribution is simplified, and leader randomly selected. This leads to problems that development exploration ability of algorithm weak rate convergence slow. Therefore, a evolutionary weight decision-making based on fuzzy control proposed in this paper. First, realize diversification regular selection wolf, dual strategy method sliding mode cross...

Some civil engineering-based infrastructures are planned for the Structural Health Monitoring (SHM) system based on their importance. Identifiction and detecting damage automatically at the right time are one of the major objectives this system faces. One of the methods to meet this objective is model updating whit use of optimization algorithms in structures.This paper is aimed to evaluate the...

The most important research area in robotics is navigation algorithms. Robot path planning (RPP) the process of choosing best route for a mobile robot to take before it moves. Finding an ideal or nearly referred as “path optimization.” solution values that satisfy single number objectives, such shortest, smoothest, and safest path, goal. objective this study present overview strategies robots u...

In order to address the problems of insufficient load capacity and rotor vibration, an active fluid-film bearing lubricated with magnetorheological fluid (MRF) is proposed. First, geometry MRF designed its intelligent lubrication mechanism analyzed clarify advantages. addition, mathematical model bearing-rotor system derived, FEM utilized obtain stiffness damping coefficients supplement model. ...